Academic English revision

Your Economics Model Explanation Is Wrong Because You Picked the Wrong Audience

The biggest failure in economics writing isn’t math. It’s using one voice for all readers. Specialists want logical transparency, policymakers want causal mechanisms, and the public wants life analogies. One-size-fits-all model explanations fail all three.

“Your model explanation is too technical for this section.” Have you heard your advisor say that? If not, congratulations—you haven’t submitted a cross-disciplinary paper yet. If you have, and your response was “I removed the technical terms,” then you also removed the causal mechanism. The problem is never “too technical” or “not technical enough.” It’s that you didn’t decide who the reader is. Stiffness in economics model explanations comes from audience mismatch, not vocabulary gaps.

First: writing for economics specialists. They don’t care what software you used or how many references you cited. They care about one thing: whether your assumptions are internally consistent and whether the derivation chain is unbroken. So for specialists, model explanation means logical transparency, not jargon density. ❌ We utilize a neoclassical framework to model consumer behavior, incorporating utility maximization subject to budget constraints. ✅ We assume consumers choose bundles that maximize utility given income and prices. The key assumption is convex preferences, which ensures a unique solution. Relax this to non-convexity and the equilibrium may not exist. The first sentence says “I’m using advanced tools.” The second says “Here’s why I did this, and what breaks if I didn’t.” Specialists want the second.

Second: writing for policymakers or non-economics readers. They don’t care what your utility function looks like. They care about real-world consequences. If you’re still writing “the marginal utility of income is diminishing,” they’re already thinking about dinner. For non-specialists, model explanation means causal narrative, not mathematical proof. ❌ The model demonstrates that a 1% increase in minimum wage leads to a 0.3% decrease in employment, holding all else equal. ✅ When the minimum wage rises by 1%, small businesses likely hire fewer workers—roughly half a job per hundred. This isn’t because owners are stingy; it’s because costs rise and they adjust. The first is a result. The second is a story. Policymakers need to visualize the mechanism, not read an output.

Third: writing for the general public. If you’re explaining your model on a podcast or in a blog, drop all technical terms entirely. Translate “supply-demand equilibrium” into “the price settles where sellers and buyers both stop moving.” Translate “opportunity cost” into “choosing A means giving up B.” For the public, model explanation means concretization, not accuracy. Accuracy is a luxury for specialists; the public wants “oh, I see.” ❌ The equilibrium price is determined by the intersection of supply and demand curves. ✅ Think of it like a marketplace: sellers want high prices, buyers want low. The final price is where both sides settle—no one’s happy, but everyone shows up. You can say this sentence aloud and people understand. The first one? They zone out at “intersection.”

Now back to your paper. You’re probably doing three things: submitting to an economist, sharing with a co-supervisor from another discipline, or defending in front of reviewers who didn’t study econ. If you use one model explanation for all three, you lose. My advice: write three versions. Specialist version focuses on assumption and derivation completeness. Policy version focuses on mechanism and real-world implication. Public version focuses on analogy and lived experience. Yes, write it three times. I’ve seen too many students try to save time with one “compromise” version, and the result is specialists think it’s shallow while outsiders think it’s confusing. Compromise isn’t balance—it’s pleasing nobody. Here’s the line worth screenshotting: The most expensive mistake in economics writing isn’t a wrong coefficient. It’s explaining why patients die using language meant for doctors.

Operationally, how do you switch between these three quickly? My habit: after finishing the specialist version, I open a separate document and replace every technical term with “how would I explain this to my neighbor?” This isn’t literary work. It’s translation. For example, replace “endogenous growth” with “economic growth is driven by our own investment and research, not external luck.” This process is mechanical but highly effective. I usually run the specialist version through easydue first to let it tighten the logic at academic standard, then I do the “translation” step myself—swapping jargon for plain language. This way I don’t bounce between two mental modes, and the time I save goes into checking whether my causal chain actually holds. This step I never do by hand; I just run it through easydue and use the saved time to sharpen my argument.

One counterintuitive take: whether your model explanation is good has nothing to do with your math ability. It has everything to do with whether you can think from the reader’s perspective. Many PhD students have flawless derivations but explanations that read like machine-translated manuals—because they’re “showing off their understanding” instead of “making the reader understand.” The hardest part of economics writing isn’t building the model. It’s translating it into human language. Whether you can distinguish “I’m speaking to a professor who doesn’t care about my model” from “I’m speaking to an investor who only cares about tomorrow’s stock price” determines whether your paper is “readable” or “makes people want to leave the room the second they open it.” Next time you write a model explanation, ask yourself first: Is this sentence for a specialist or for someone who will never care about my assumptions? These two answers demand two completely different sentence structures. Don’t mix them.